Image recognition systems, also known as object classification systems, analyze data representing an image, also known as image data. Based on the analysis, an image recognition system may output one or more objects or features that may be present in the image. In addition, confidence values or scores for each of the one or more objects or features may also be output. Confidence values, which are numerical values, may range from 0 to 1, where a value of 1 indicate greatest correlation and a value of 0 indicates no correlation. The confidence values in an output distribution may be ranked highest to lowest based on the likelihood that the object or feature is depicted in the image. The confidence values may be utilized to disambiguate the image data into objects or features present in the image. Image recognition systems may utilize rule-based artificial intelligence and information retrieval systems to identify and assign values to candidate objects or features. Image recognition systems may comprise convolutional neural networks or other types of networks that provide the intended results.